Named Entity Recognition Ner On Ontonotes V5
Metrics
F1
Results
Performance results of various models on this benchmark
Model Name | F1 | Paper Title | Repository |
|---|---|---|---|
| Syn-LSTM + BERT (wo doc-context) | 90.85 | - | - |
| DGLSTM-CRF + ELMo | 89.88 | - | - |
| BiLSTM-LAN | 88.16 | - | - |
| Bi-LSTM-CRF + Lexical Features | 87.95 | - | - |
| PL-Marker | 91.9 | - | - |
| Syn-LSTM (wo doc-context) | 89.04 | - | - |
| BERT-MRC | 91.11 | - | - |
| Hierarchical | 87.98 | - | - |
| BiLSTM-CRF | 86.99 | - | - |
| DGLSTM-CRF (L=2) | 88.52 | - | - |
| Joint Model | 84.04 | - | - |
| Biaffine-NER | 91.3 | - | - |
| CVT + Multi-Task + Large | 88.81 | - | - |
| HSCRF + softdict | 89.94 | - | - |
| Att-BiLSTM-CNN | 88.4 | - | - |
| BARTNER | 90.38 | - | - |
| NuNER | 89.1 | - | - |
| W2NER | 90.50 | - | - |
| AESINER | 90.32 | - | - |
| GRN | 87.67 | - | - |
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